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Environmental life cycle assessment of grain maize production: An analysis of factors causing variability. / Boone, Lieselot; Van linden, Veerle; De Meester, Steven; Vandecasteele, Bart; Muylle, Hilde; Roldán-Ruiz, Isabel; Nemecek, Thomas; Dewulf, Jo.

In: Science of the Total Environment, Vol. 553, 03.2016, blz. 551-564.

Onderzoeksoutput: Bijdrage aan tijdschriftA1: Web of Science-artikelOnderzoekpeer review

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@article{958b6f597f294e428fa47dffd2217e2b,
title = "Environmental life cycle assessment of grain maize production: An analysis of factors causing variability",
abstract = "To meet the growing demand, high yielding, but environmentally sustainable agricultural plant production systems are desired. Today, life cycle assessment (LCA) is increasingly used to assess the environmental impact of these agricultural systems. However, the impact results are very diverse due to management decisions or local natural conditions. The impact of grain maize is often generalized and an average is taken. Therefore,we studied variation in production systems. Four types of drivers for variability are distinguished: policy, farm management, year-to-yearweather variation and innovation. For each driver, scenarios are elaborated using ReCiPe and CEENE (Cumulative Exergy Extraction from the Natural Environment) to assess the environmental footprint. Policy limits fertilisation levels in a soil-specific way. The resource consumption is lower for non-sandy soils than for sandy soils, but entails however more eutrophication. Farmmanagement seems to have less influence on the environmental impact when considering the CEENE only. But farm management choices such as fertiliser type have a large effect on emission-related problems (e.g. eutrophication and acidification). In contrast, year-to-year weather variation results in large differences in the environmental footprint. The difference in impact results between favourable and poor environmental conditions amounts to 19{\%} and 17{\%} in terms of resources and emissionsrespectively, and irrigation clearly is an unfavourable environmental process. The best environmental performance is obtained by innovation as plant breeding results in a steadily increasing yield over 25 years.Finally, a comparison is made between grain maize production in Flanders and a generically applied dataset, based on Swiss practices. These very different results endorse the importance of using local data to conduct LCA of plant production systems. The results of this study show decision makers and farmers how they can improve the environmental performance of agricultural systems, and LCA practitioners are alerted to challenges due to variation.",
author = "Lieselot Boone and {Van linden}, Veerle and {De Meester}, Steven and Bart Vandecasteele and Hilde Muylle and Isabel Rold{\'a}n-Ruiz and Thomas Nemecek and Jo Dewulf",
year = "2016",
month = "3",
language = "English",
volume = "553",
pages = "551--564",
journal = "Science of the Total Environment",
issn = "0048-9697",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Environmental life cycle assessment of grain maize production: An analysis of factors causing variability

AU - Boone, Lieselot

AU - Van linden, Veerle

AU - De Meester, Steven

AU - Vandecasteele, Bart

AU - Muylle, Hilde

AU - Roldán-Ruiz, Isabel

AU - Nemecek, Thomas

AU - Dewulf, Jo

PY - 2016/3

Y1 - 2016/3

N2 - To meet the growing demand, high yielding, but environmentally sustainable agricultural plant production systems are desired. Today, life cycle assessment (LCA) is increasingly used to assess the environmental impact of these agricultural systems. However, the impact results are very diverse due to management decisions or local natural conditions. The impact of grain maize is often generalized and an average is taken. Therefore,we studied variation in production systems. Four types of drivers for variability are distinguished: policy, farm management, year-to-yearweather variation and innovation. For each driver, scenarios are elaborated using ReCiPe and CEENE (Cumulative Exergy Extraction from the Natural Environment) to assess the environmental footprint. Policy limits fertilisation levels in a soil-specific way. The resource consumption is lower for non-sandy soils than for sandy soils, but entails however more eutrophication. Farmmanagement seems to have less influence on the environmental impact when considering the CEENE only. But farm management choices such as fertiliser type have a large effect on emission-related problems (e.g. eutrophication and acidification). In contrast, year-to-year weather variation results in large differences in the environmental footprint. The difference in impact results between favourable and poor environmental conditions amounts to 19% and 17% in terms of resources and emissionsrespectively, and irrigation clearly is an unfavourable environmental process. The best environmental performance is obtained by innovation as plant breeding results in a steadily increasing yield over 25 years.Finally, a comparison is made between grain maize production in Flanders and a generically applied dataset, based on Swiss practices. These very different results endorse the importance of using local data to conduct LCA of plant production systems. The results of this study show decision makers and farmers how they can improve the environmental performance of agricultural systems, and LCA practitioners are alerted to challenges due to variation.

AB - To meet the growing demand, high yielding, but environmentally sustainable agricultural plant production systems are desired. Today, life cycle assessment (LCA) is increasingly used to assess the environmental impact of these agricultural systems. However, the impact results are very diverse due to management decisions or local natural conditions. The impact of grain maize is often generalized and an average is taken. Therefore,we studied variation in production systems. Four types of drivers for variability are distinguished: policy, farm management, year-to-yearweather variation and innovation. For each driver, scenarios are elaborated using ReCiPe and CEENE (Cumulative Exergy Extraction from the Natural Environment) to assess the environmental footprint. Policy limits fertilisation levels in a soil-specific way. The resource consumption is lower for non-sandy soils than for sandy soils, but entails however more eutrophication. Farmmanagement seems to have less influence on the environmental impact when considering the CEENE only. But farm management choices such as fertiliser type have a large effect on emission-related problems (e.g. eutrophication and acidification). In contrast, year-to-year weather variation results in large differences in the environmental footprint. The difference in impact results between favourable and poor environmental conditions amounts to 19% and 17% in terms of resources and emissionsrespectively, and irrigation clearly is an unfavourable environmental process. The best environmental performance is obtained by innovation as plant breeding results in a steadily increasing yield over 25 years.Finally, a comparison is made between grain maize production in Flanders and a generically applied dataset, based on Swiss practices. These very different results endorse the importance of using local data to conduct LCA of plant production systems. The results of this study show decision makers and farmers how they can improve the environmental performance of agricultural systems, and LCA practitioners are alerted to challenges due to variation.

UR - http://dx.doi.org/10.1016/j.scitotenv.2016.02.089

M3 - A1: Web of Science-article

VL - 553

SP - 551

EP - 564

JO - Science of the Total Environment

JF - Science of the Total Environment

SN - 0048-9697

ER -